最近Feed-forward GS的工作爆发了

Core Viewpoint - The article emphasizes the rapid advancements in 3D Gaussian Splatting (3DGS) technology within the autonomous driving sector, highlighting the need for structured learning pathways for newcomers in the field [2][4]. Group 1: Technology Highlights - Tesla's introduction of 3D Gaussian Splatting at ICCV has garnered significant attention, indicating a shift towards feed-forward GS algorithms for scene reconstruction [2]. - The iterative development of 3DGS technology includes static 3D reconstruction, dynamic 4D reconstruction, and surface reconstruction, showcasing its evolving nature [4]. Group 2: Course Offering - A comprehensive course titled "3DGS Theory and Algorithm Practical Tutorial" has been designed to provide a structured learning roadmap for 3DGS, covering both theoretical foundations and practical applications [4]. - The course will be taught by an expert with extensive experience in 3D reconstruction and algorithm development, ensuring high-quality instruction [5]. Group 3: Course Structure - The course consists of six chapters, starting with foundational knowledge in computer graphics and progressing through principles, algorithms, and specific applications in autonomous driving [8][9][10][11][12]. - Each chapter is designed to build upon the previous one, culminating in discussions about current industry needs and research directions in 3DGS [11][12][13]. Group 4: Target Audience and Prerequisites - The course is aimed at individuals with a background in computer graphics, visual reconstruction, and programming, particularly those interested in pursuing careers in the autonomous driving industry [17]. - Participants are expected to have a foundational understanding of relevant mathematical concepts and programming languages, which will facilitate their learning experience [17].